%0 Conference Proceedings
%T Date Estimation in the Wild of Scanned Historical Photos: An Image Retrieval Approach
%A Adria Molina
%A Pau Riba
%A Lluis Gomez
%A Oriol Ramos Terrades
%A Josep Llados
%B 16th International Conference on Document Analysis and Recognition
%D 2021
%V 12822
%F Adria Molina2021
%O DAG; 600.121; 600.140; 110.312
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3571), last updated on Mon, 24 Oct 2022 12:30:43 +0200
%X This paper presents a novel method for date estimation of historical photographs from archival sources. The main contribution is to formulate the date estimation as a retrieval task, where given a query, the retrieved images are ranked in terms of the estimated date similarity. The closer are their embedded representations the closer are their dates. Contrary to the traditional models that design a neural network that learns a classifier or a regressor, we propose a learning objective based on the nDCG ranking metric. We have experimentally evaluated the performance of the method in two different tasks: date estimation and date-sensitive image retrieval, using the DEW public database, overcoming the baseline methods.
%U http://refbase.cvc.uab.es/files/MRG2021b.pdf
%U http://dx.doi.org/10.1007/978-3-030-86331-9_20
%P 306-320